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                <div class="bbp-reply-header" id="post-232781">
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                   2007年9月3日 下午3:28
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/7657/">
                    我打赌,你小时侯肯定写过这句话……
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                   need some entertainment again
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                   2007年9月3日 下午3:17
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/7671/">
                    求助[ 如何确定资料是否为正态分布]
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                    [b]引用第0楼[i]hejin0315[/i]于[i]2007-09-03 00:39[/i]发表的“求助[ 如何确定资料是否为正态分布]”[/b]:
                    <br/>
                    如何确定资料是否为正态分布
                   </p>
                  </blockquote>
                  <p>
                   ｀正态分布与否｀－这与你的调查设计及性质很有关系。本人建议，请看｀research methods'相关资料再结合统计探讨normal distribution的问题吧。
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                   2007年9月3日 下午3:09
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/7682/">
                    求助:likert scale 的问题可以用SPSS里的什么方法分析啊
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                    [b]引用第0楼[i]jessie0310[/i]于[i]2007-09-03 19:46[/i]发表的“求助:likert scale 的问题可以用SPSS里的什么方法分析啊”[/b]:
                    <br/>
                    各位高手们,紧急求助啊,小妹最近在写毕业论文中,自己做了问卷,可是在分析中遇到了大难题
                    <br/>
                    题目:
                    <br/>
                    您认为下列因素对获得银行融资起了什么作用?(1=非常大的促进作用,2=有促进作用,3=不好说,4=阻碍作用,5=非常大的阻碍作用)
                    <br/>
                    A. 政府的偏向性
                    <br/>
                    B. 银行不愿意
                    <br/>
                    …….
                   </p>
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                  <p>
                   有几点个人看法想与你分享。首先，对于问题“求助:likert scale 的问题可以用SPSS里的什么方法分析啊”，这不是个有'意义'的问题，或者说你的问题问得不正确。因为这个问题不是在乎'likert scale'用spss什么方法去分析的。spss只是个程序，等于Microsoft word一样，你要会用（比如说打字），word才可以发挥其本身作用。同样地，spss只会按你的命令去运作，所以，你应该从自己想打什么字（即，你想分析什么）入手。
                  </p>
                  <p>
                   第二，分析目的：你的分析方法服务于你的分析目的。你的目的是。。。？
                  </p>
                  <p>
                   另，草草看了一下你的问卷，有疑问：你的scale是否在全卷中都使用的？A,B,C…are various dimensions of ｀银行融资｀？ How many of them, please?
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                   2007年9月1日 上午8:34
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/7608/">
                    求助：SPSS可以对回归正交设计试验进行回归分析么
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                   7 楼
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                   Linda, you meant how to use regression in SPSS? What do you want to regress from?? Perhaps some details about your variables, please?
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                   2007年9月1日 上午8:30
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/7291/">
                    新手请教关于判别分析的问题
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                    [b]引用第0楼[i]neunux[/i]于[i]2007-08-05 22:39[/i]发表的“新手请教关于判别分析的问题”[/b]:
                    <br/>
                    有一个比较初级的问题。判别分析对case数有要求吗？比如必须多少以上？如果数量比较少，比如10个，但是得到的判别函数显著，并且在判别新样本时正确率在70%以上，是否可以接受？谢谢！！
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                  <p>
                   Discriminant analysis has requirement regarding the number of cases. The common questions are related to the number of IVs, unequal sample sizes, classification and prediction. There is no explicit answer to your question (i.e. 比如必须多少以上) as it depends on various factors, such as the whole sample size.
                  </p>
                  <p>
                   Some issues for you to consider: how many IVs do you have? What are the number of cases in each of these IVs? How big is your sample? These questions are vital to justify the outcome of discriminant analysis. I personally belive that it is inappropriate to give any comment on the outcome of your analysis without having a thorough understanding of your research nature, such as the questions mentioned above.
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                   Your second question (i.e. 在判别新样本时正确率在70%以上) is very much depending on the way how you want to classify the cases. which method do you use for classfication, 'prior probability' or 'sample size'? Again, an objective manner is important when you evaluate the outcome of discriminant analysis such as adequate classification rate and 'significant importance'. If you may provide more details regarding the above questions, perhaps more proper discussion and hopefully suggestion may be generated.
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                   Good luck.
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                   2007年8月30日 上午10:13
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/7554/">
                    关于质量改进的问题!
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                  <p>
                   To Danny Liu
                   <br/>
                   PCA and FA are not quite the same. They are two different techniques and work on different purposes and analytical approaches, although quite often, they would produce similar results. One fundamental difference in relation to analysis purpose is that PCA is often recommended for data reduction while FA is to detect the underlying structure of the variables.
                  </p>
                  <p>
                   Also, FA works on a mathematical model and factors may be estimated. On the other hand, PCA simply transforms your original variables into a new set of linear combinations (that's why they called the principal components) (Stevens, 1992: p375).
                  </p>
                  <p>
                   If you may get hold of this book [by Tabachnick, B. G. and Fidell, L. S. (1989), Using Multivariate Statistics (2nd), Harper Collins Publishers, U.S.A ], you may learn more about these two techniques. Good luck.
                  </p>
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                <div class="bbp-reply-header" id="post-231966">
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                  <span class="bbp-reply-post-date">
                   2007年8月27日 下午12:24
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/7482/">
                    请教:SPSS中的分组回归
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                  <p>
                   A question for you: which approach of regression are you applying, standard, hierarchical or multiple regression?
                  </p>
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                <div class="bbp-reply-header" id="post-231965">
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                   2007年8月27日 下午12:20
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/7482/">
                    请教:SPSS中的分组回归
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                   4 楼
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                  <p>
                   Compare the tables of ANOVA and model summary between your groups, I think.
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                <div class="bbp-reply-header" id="post-231517">
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                   2007年8月21日 上午11:29
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/7411/">
                    求教一spss分组问题
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                  <p>
                   It's easy to transform data in SPSS; however, you should have a sound argument for your decision. The transformation process is:
                   <br/>
                   1. Transform
                   <br/>
                   2. Record
                   <br/>
                   3. Into same variables or into different variables.
                  </p>
                  <p>
                   Good luck.
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                <div class="bbp-reply-header" id="post-231516">
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                   2007年8月21日 上午11:23
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                   回复：
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                    请教:SPSS中的分组回归
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                  <p>
                   Data split procedure:
                   <br/>
                   1. click on the 'Data menu'
                   <br/>
                   2. choose 'Split file'
                   <br/>
                   3. click on 'compare groups' and specify your grouping variable (e.g. gender, age etc.)
                   <br/>
                   4. click on 'ok'
                  </p>
                  <p>
                   Three main steps for regression (if my brain is working properly):
                   <br/>
                   1. Check the assumptions: multicollinearity. Check correlations between dependent and independent variables. There should be some association between the variables, however, it may also be problematic if the correation is too high/low. 'Collinearity diagnostics' needs to be checked as well. The checking of other assumptions is also important, including outliers, independence of residuals and so on.
                  </p>
                  <p>
                   2. Evaluating the model: Model summary (R² and adjusted R²). Statistical significance of the regression: ANOVA.
                  </p>
                  <p>
                   3. Assessing each of the independent variables (Coefficients).
                  </p>
                  <p>
                   Good luck with your analysis.
                  </p>
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                <div class="bbp-reply-header" id="post-228435">
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                   2007年6月30日 下午2:28
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/6922/">
                    关于客户细分 差异检验的疑问
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                   <p>
                    [b]引用第3楼[i]melodygd[/i]于[i]2007-06-30 20:33[/i]发表的“”[/b]:
                    <br/>
                    多谢anita_jiu的提醒。 我的具体问题是： 对一类客户群体做满意度在性别方面的差异分析。做方差分析后，发现该客户群的满意度在性别上没有差异。如果我对该类客群根据其他属性（比如年龄）做进一步细分，那么，细分出来的各个客群的满意度在性别上有可能存在差异吗？
                   </p>
                   <p>
                    简单的说就是， 对于在某个个人属性上同质的客户群体，在按照其他一些个人属性细分为更小的客户群体后，这些客户群体在原来那个个人属性上可能存在差异吗？
                   </p>
                   <p>
                    不知说没说清楚。还请高人指点。
                   </p>
                  </blockquote>
                  <p>
                   Thanks for the details. I think that nothing (in general) would stop you playing with your data. This means, yes, certainly you may continue to try to identify any difference exists in your sample through elements such as age, gender, education, income, family status etc. However, I'd like to point out one thing: so what? This is a key question to answer. Have found or haven't found difference, so what? If statistical difference exists, does it have any impact on the practical side? Does it help marketers and researchers better understand your particular market?? Any implications for marketers and/or researchers?
                  </p>
                  <p>
                   By the way, more questions to come: in general, is your sample a homogeneous sample (i.e. share commonalities) or not, please? How big is your sample? The nature of your sample also affects statistic analysis outcomes. I'd suggest you review your research objectives at this point.
                  </p>
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                <div class="bbp-reply-header" id="post-228405">
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                   2007年6月29日 下午2:36
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/5849/">
                    有关factor analysis的问题
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                   7 楼
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                   <p>
                    [b]引用第5楼[i]laurayan[/i]于[i]2007-05-25 21:19[/i]发表的“”[/b]:
                    <br/>
                    做因子分析的时候用SPSS求出了KMO和Bartlett球体检验两个P值后，后面一定要将各项目在共同分子上的负荷量求出、进一步分类吗？
                   </p>
                   <p>
                    我觉得根据负荷量进一步分类好麻烦，往往到了这一步就不知所措了。
                   </p>
                   <p>
                    如果只求得两个P值并给出各项目的负荷量、但是并不根据其进行分类，这样的因子分析是否根本还无法说明问卷的效度呢？
                   </p>
                  </blockquote>
                  <p>
                   1. KMO and Bartlett tests are applied to examine whether your data is approapriate for factor analysis. Outcomes of these tests are important because they tell you whether factory analysis should be carried on or not.
                  </p>
                  <p>
                   2. If these tests tell you that your data is approapriate for factor analysis, then you need to determine what variables should be considered in factor analysis. This is simply because of a well-known expression in relation to the analysis: "Garbage in, garbage out". As a software, SPSS works on the data you input into its 'stomache'. All right?
                  </p>
                  <p>
                   3. Decide whether you want to conduct exploratory factor analysis or confirmatory factor analysis – they both may help examine dimension validity but on different purposes. You need to decide.
                  </p>
                  <p>
                   4. You should also be ready to answer a number of common questions:
                   <br/>
                   which extraction method, e.g. for exploratory purpose, principal components analysis or common factor analysis?,
                   <br/>
                   which rotation method,
                   <br/>
                   how many factors,
                   <br/>
                   factor loading values.
                  </p>
                  <p>
                   Software is just software; researchers should be well prepared to make justifiable decisions.
                  </p>
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                   2007年6月29日 下午2:22
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/6924/">
                    不定项选择的录入与分析？
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                  <p>
                   You meant given a number of answers to your respondents, they are allowed to choose more than one answer; and now you are not sure how to input the data into SPSS?
                  </p>
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                <div class="bbp-reply-header" id="post-228402">
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                   2007年6月29日 下午2:19
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/6922/">
                    关于客户细分 差异检验的疑问
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                   3 楼
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                  <blockquote class="d4pbbc-quote">
                   <p>
                    [b]引用第0楼[i]melodygd[/i]于[i]2007-06-29 15:21[/i]发表的“关于客户细分 差异检验的疑问”[/b]:
                    <br/>
                    请问： 也就是，如果抽样的客群总体在某属性上无差异的话，其中的部分客群是否还会在该属性上存在显著差异？
                   </p>
                   <p>
                    比如，对一类客户群体做性别的差异分析，发现该客户群中没有性别的差异。那么，是否有必要对该类客群根据其他属性做进一步细分，看细分后的各客群是否存在性别差异？
                   </p>
                   <p>
                    …….
                   </p>
                  </blockquote>
                  <p>
                   某属性 – what element exactly, pls? Is it related to demographical elements (e.g. income, age) or something else, please (e.g. purchase behaviour)? Would you mind giving more details about your sample or research, please? Otherwise it is difficult to discuss your question on a sound ground.
                  </p>
                  <p>
                   There are arguments for using homogeneous sample; then of course, there are also debates against this application. It depends on your research nature. If you may explain a bit more, perhaps it would be helpful for others to interact your query more appropriately.
                  </p>
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                <div class="bbp-reply-header" id="post-227974">
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                   2007年6月21日 下午4:55
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                   回复：
                   <a class="bbp-topic-permalink" href="http://cos.name/cn/topic/6764/">
                    请教：spss能做哪些多元统计？
                   </a>
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                   4 楼
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                    [b]引用第0楼[i]chinasun[/i]于[i]2007-06-15 11:14[/i]发表的“请教：spss能做哪些多元统计？”[/b]:
                    <br/>
                    请教：spss提供了多少可供多元统计分析的程序，用它做多元统计分析，在结果上与专门的多元统计分析软件有没有区别？
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                   1. Wondering why difference would be generated?
                   <br/>
                   2. Perhaps for competitive advantage purpose, like many other statistic software, SPSS is designed to process some (but not all) multivirate statistic analysis. Sometimes even within the same analysis (e.g. factor analysis), some particular techniques are not available in SPSS.
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